The writer of this code wants to count the mean and median article length for recent articles on gay marraige. This code has several issues, including errors. When they checked their custom functions against the numpy functions, they noticed some discrepancies. Fix the code so it executes properly and the output of the custom functions match the output of the numpy functions

In [5]:

    

import requests # a better package than urllib2


    

In [6]:

    

def my_mean(input_list):
    list_sum = 0
    list_count = 0
    for el in input_list:
        list_sum += el
        list_count += 1
    return list_sum / float(list_count) # cast list_count to float


    

In [42]:

    

def my_median(input_list):
    input_list.sort() # sort the list
    list_length = len(input_list) # get length so it doesn't need to be recalculated

    # test for even length and take len/2 and len/2 -1 divided over 2.0 for float division
    if list_length %2 == 0: 
        return (input_list[list_length/2] + input_list[(list_length/2) - 1]) / 2.0 
    else:
        return input_list[list_length/2]


    

In [2]:

    

api_key = "ffaf60d7d82258e112dd4fb2b5e4e2d6:3:72421680"


    

In [3]:

    

url = "http://api.nytimes.com/svc/search/v2/articlesearch.json?q=gay+marriage&api-key=%s" % api_key # variable name mistyped


    

In [8]:

    

r = requests.get(url)


    

In [10]:

    

wc_list = []
for article in r.json()['response']['docs']:
    wc_list.append(int(article['word_count'])) #word_count needs to be cast to int


    

In [11]:

    

my_mean(wc_list)


    

    
Out[11]:





1034.2

In [12]:

    

import numpy as np


    

In [13]:

    

np.mean(wc_list)


    

    
Out[13]:





1034.2

In [43]:

    

my_median(wc_list)


    

    
Out[43]:





926.5

In [28]:

    

np.median(wc_list)


    

    
Out[28]:





926.5